Updated thesis

src/training_scripts/autoregressive_quantiles.py

@@ -52,7 +52,7 @@ data_processor.set_full_day_skip(False)
 #### Hyperparameters ####
 data_processor.set_output_size(1)
 inputDim = data_processor.get_input_size()
-epochs = 300
+epochs = 16
 
 # add parameters to clearml
 quantiles = task.get_parameter("general/quantiles", cast=True)

src/training_scripts/diffusion_training.py

@@ -2,7 +2,7 @@ from src.utils.clearml import ClearMLHelper
 
 clearml_helper = ClearMLHelper(project_name="Thesis/NrvForecast")
 task = clearml_helper.get_task(
-    task_name="Diffusion Training: hidden_sizes=[1024, 1024, 1024, 1024] (300 steps), lr=0.0001, time_dim=8"
+    task_name="Diffusion Training: hidden_sizes=[2048, 2048, 2048, 2048] (300 steps), lr=0.0001, time_dim=8"
 )
 task.execute_remotely(queue_name="default", exit_process=True)
 
@@ -42,7 +42,7 @@ print("Input dim: ", inputDim)
 model_parameters = {
     "epochs": 15000,
     "learning_rate": 0.0001,
-    "hidden_sizes": [1024, 1024, 1024, 1024],
+    "hidden_sizes": [2048, 2048, 2048, 2048],
     "time_dim": 8,
 }